AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Esophageal Neoplasms

Showing 171 to 180 of 250 articles

Clear Filters

Artificial intelligence for the detection of esophageal and esophagogastric junctional adenocarcinoma.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Conventional endoscopy for the early detection of esophageal and esophagogastric junctional adenocarcinoma (E/J cancer) is limited because early lesions are asymptomatic, and the associated changes in the mucosa are subtle. There ...

Utilizing artificial intelligence in endoscopy: a clinician's guide.

Expert review of gastroenterology & hepatology
INTRODUCTION: Artificial intelligence (AI) that surpasses human ability in image recognition is expected to be applied in the field of gastrointestinal endoscopes. Accordingly, its research and development (R &D) is being actively conducted. With the...

Robot-Assisted Minimally Invasive Esophagectomy with Intrathoracic Anastomosis (Ivor Lewis): Promising Results in 100 Consecutive Patients (the European Experience).

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Robot-assisted minimally invasive esophagectomy (RAMIE) with intrathoracic anastomosis is gaining popularity as a treatment for esophageal cancer. The aim of this study was to describe postoperative complications and short-term oncologic ...

A novel deep learning model using dosimetric and clinical information for grade 4 radiotherapy-induced lymphopenia prediction.

Physics in medicine and biology
Radiotherapy-induced lymphopenia has increasingly been shown to reduce cancer survivorship. We developed a novel hybrid deep learning model to efficiently integrate an entire set of dosimetric parameters of a radiation treatment plan with a patient's...

Machine learning to predict early recurrence after oesophageal cancer surgery.

The British journal of surgery
BACKGROUND: Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20-30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This s...

Deep principal dimension encoding for the classification of early neoplasia in Barrett's Esophagus with volumetric laser endomicroscopy.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Barrett cancer is a treatable disease when detected at an early stage. However, current screening protocols are often not effective at finding the disease early. Volumetric Laser Endomicroscopy (VLE) is a promising new imaging tool for finding dyspla...

Technique for Robotic Transhiatal Esophagectomy.

Annals of surgical oncology
Minimally invasive esophagectomy is increasing performed for cancers of the esophagus and gastroesophageal junction. This video demonstrates the setup and key steps for a robotic transhiatal esophagectomy with a cervical anastomosis.

Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett's esophagus (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The visual detection of early esophageal neoplasia (high-grade dysplasia and T1 cancer) in Barrett's esophagus (BE) with white-light and virtual chromoendoscopy still remains challenging. The aim of this study was to assess wheth...

Deep learning algorithm detection of Barrett's neoplasia with high accuracy during live endoscopic procedures: a pilot study (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: We assessed the preliminary diagnostic accuracy of a recently developed computer-aided detection (CAD) system for detection of Barrett's neoplasia during live endoscopic procedures.